• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.472-473
• /
• 2008

심실조기수축(PVC: Premature Ventricular Contraction)은 성인에게서 가장 흔하게 발생되는 심장 부정맥 증상 중의 하나이다. 심실조기수축 부정맥이 자주 발현되는 사람의 경우 관상 동맥질환, 고혈압 등의 심혈관계 질환이 진행되고 있을 가능성이 많고, 심실빈맥이나 심실세동으로 전이되는 경우 심정지 등을 유발하여 사망에 이르기 때문에 지속적으로 관찰이 필요한 증상이다. 따라서 본 연구에서는 R-R 간격 정보를 이용하여 심실조기수축 부정맥 증상을 실시간으로 검출할 수 있는 신호처리 알고리즘을 구현하고자 하였다.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.44 no.5
• /
• pp.45-54
• /
• 2007

Time/frequency analysis has been extensively used in biomedical signal processing. By extracting some essential features from the electro-physiological signals, these methods are able to determine the clinical pathology mechanisms of some diseases. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. In this paper, we develop a new signal processing method using Hilbert-Huang Transform to perform analysis of the nonlinear and non-stationary ventricular fibrillation(VF). Hilbert-Huang Transform combines two major analytical theories: Empirical Mode Decomposition(EMD) and the Hilbert Transform. Hilbert-Huang Transform can be used to decompose natural data into independent Intrinsic Mode Functions using the theories of EMD. Furthermore, Hilbert-Huang Transform employs Hilbert Transform to determine instantaneous frequency and amplitude, and therefore can be used to accurately describe the local behavior of signals. This paper studied for Return Of Spontaneous Circulation(ROSC) and non-ROSC prediction performance by Support Vector Machine and three parameters(EMD-IF, EMD-FFT) extracted from ventricular fibrillation ECG waveform using Hilbert-Huang transform. On the average results of sensitivity and specificity were 87.35% and 76.88% respectively. Hilbert-Huang Transform shows that it enables us to predict the ROSC of VF more precisely.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.1665-1668
• /
• 2008

Arrhythmia causes sudden cardiac death. In the past, there were medical limitations in finding the cause of arrhythmia. As an alternative solution for research of arrhythmia, there have been studies to find the causes of arrhythmia by producing a virtual heart model. Medically, arrhythmia has two main causes: abnormal occurrence of action potential and abnormal conduction of action potential. Based on these, the tachycardia, which is one of the arrhythmia, was manifested and the phenomenon of ventricular fibrillation was numerically analyzed in this study. For this purpose, an electrophysiological model of ventricular cells was implemented, which was subsequently applied to the reaction-diffusion partial differential equation to interpret the macroscopic conduction phenomenon in two-dimensional tissues. The ventricular fibrillation refers to a condition where several irregular waves occur in cardiac tissue, whose generation mechanism is pathologically related to the cardiac tissue.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.2 no.2
• /
• pp.15-21
• /
• 2009

This paper proposes a novel algorithm to assess the abnormal heart beats such as PVC (Premature Ventricular Contraction) and its subsequent RUNs. Our Arrhythmic detection scheme is based on only the R-R Interval features extracted from ECG waveforms and MIT-BIH arrhythmia database is evaluated to validate the efficiency of our algorithm in terms of sensitivity, specificity, FPR(%) and FNR(%).

• Proceeding of EDISON Challenge
• /
• 2017.03a
• /
• pp.662-664
• /
• 2017

심실 내부에 가해지는 수축력에 의해 심실 내부 벽에는 큰 무리가 될 수 있다. 이로 인해 다양한 심장질환인 부정맥, 심실 세동 등을 유발한다. 따라서 본 연구에서는 가상 심장모델을 구축하여 컴퓨터 시뮬레이션을 통한 수축이완시의 심장 상태를 살펴보고자 하였다. 이를 위해서 개 심장 모델을 활용하여 3차원으로 이뤄진 심장모델을 구현하였다. 심장모델의 전기생리학 기전에 기초한 전기전도 해석을 수행하고, 전기전도 해석 시 발생되는 칼슘이온의 농도변화를 활용하였다. 시간에 따른 칼슘 이온의 심장 수축 영향을 바탕으로 비선형 유한요소법을 이용, 3차원 심장의 수축역학을 해석하였다. 이러한 기전으로 심장 근육에 부하되는 응력(tension)를 계산하고, 이렇게 계산된 심근의 응력분포에 대해 관측 및 분석을 진행하였다.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.393-395
• /
• 2009

심장의 활성 근육의 움직임에 의하여 발생되는 전기적 변화량을 나타내는 심전도는 부정맥 또는 허혈성 심장질환을 진단하는데 널리 활용되고 있다. 특히 심실빈맥(Ventricular Tachycardia) 또는 심실세동(Ventricular Fibrillation)과 같이 치명적인 심장리듬이 발생하기 이전에, 심실조기수축(Ventricular Premature Contraction)을 검출하여 생명을 위협할 수 있는 부정맥을 조기에 진단할 수 있는 연구들이 일부 진행되고 있다. 이에 따라서 본 연구에서는 심전도 신호의 R-R 간격 정보와 R-peak 정보의 진위성을 판단하여 PVC 부정맥 패턴뿐만 아니라 PVC 파형이 연속적으로 진행되는 PVC-RUNs을 효율적으로 검출할 수 있는 부정맥 진단 알고리즘을 제안하고자 하였다.

• Journal of Sensor Science and Technology
• /
• v.6 no.3
• /
• pp.245-251
• /
• 1997

In designing defibrillator, several parameters such as patient's transthoracic impedance, output energy level, peak current, and time duration of current waveform must be considered to generate optimum electrical shocks on the heart. Patient's transthoracic impendence depends on the physical and health condition of patient. In this study, before the development of a defibrillator, the range of above parameters value as circuit elements was determined to derive optimal waveform by predicting and analyzing the performance of designed circuit by means of simulation with the software, P-Spice. The efficiency of parameter design was verified through the performance test with the developed defibrillator.

• Journal of Korean Academy of Nursing Administration
• /
• v.15 no.2
• /
• pp.203-215
• /
• 2009

Purpose: In order to improve resuscitation rate of CPR through providing qualitative nursing while performing CPR in hospital ward and to enhance quality of emergency nursing in the ward, the author embarked on the research as a way of developing ventricular fibrillation protocol about CPR. Method: Collected data were analyzed by using the SPSS/PC14.0 program while the routes of final protocol developed in this research are as follows. Result: Based on analysis results of literature study and CPR electronic hospital records, a total of 22 items and 53 specific contents were confirmed through the gathering of opinions from panels, and the allotment of roles and tasks with a standard of 2 nurses was designated. As the result of specialists' verification on validity, the final protocol composed of a total of 23 items and 45 specific contents was confirmed. At the result of the pertinency evaluation of confirmed protocol, it was evaluated as relatively pertinent with its average score 2.89-3.32. Conclusion: The protocol developed in this research is seen as to contribute to nurses participating in CPR to avoid the overlapping of tasks and to develop CPR through effective teamwork of medical teams by presenting clear roles and tasks.

• Journal of Chest Surgery
• /
• v.39 no.12 s.269
• /
• pp.931-933
• /
• 2006

Robotic assisted surgery in adult patient with congenital ventricular septal defect Since December in 2005, we have done minimally invasive surgeries in selected cases of mitral valve diseases, tricuspid valve diseases, atrial septal defects and atrial fibrillations with the $AESOP^{TM}$ robotic arm. We have had a better surgical view and skill, according to accumulation of the experience of this procedure. Recently, we performed robotic assisted surgery in a 47-year-old female with congenital perimembranous ventricular septal defect.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.9
• /
• pp.2021-2030
• /
• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.